Baseline Methodology for Energy Sector CDM Projects by Dr. Govinda R. Timilsina

1. Baseline Methodology for Energy Sector CDM Projects by Dr. Govinda R. Timilsina Energy & Climate Change Specialist RegionalWorkshop on CapacityBuilding for CDM 24-26 March 2004 Siem Reap, Cambodia

2. Introduction New Baseline Methodologies (Submitted and Approved) Steps to adopt and develop baseline methodologies Examples of Baseline Methodology for Energy Sector CDM Projects Models for Baseline Emission Estimation Presentation Outline

3. What is a baseline? The Paragraph 5c of the Article 12 of the Kyoto Protocol states that emission reductions from a CDM project should be additional to any that would occur in the absence of such activities. The best guess as to what would have happened in the absence of a CDM project activity is referred to as baseline for the project. The Marrakech Accord defines the baseline as the scenario that reasonably represents the anthropogenic emissions by sources of greenhouse gases that would occur in the absence of the proposed project activity. INTRODUCTION

4. The paragraph 48 of the modalities and procedures for the clean development mechanism suggests the following three approaches for choosing a baseline methodology for a CDM project activity: Existing actual or historical emissions, as applicable; Emissions from a technology that represents an economically attractive course of action, taking into account barriers to investment; The average emissions of similar project activities undertaken in the previous five years, in similar social, economic, environmental and technological circumstances, and whose performance is among the top 20 per cent of their category. INTRODUCTION (Cont..)

5. Since January 2003 to February 2004, a total 45 new baseline methodologies have been submitted to the CDM EB. Of which nine are approved, nine are not approved and the rest 27 are under various stages of review process. Types of Projects for New Baseline Methodologies Submitted: Biomass Fired Co-generation Landfill Gas Capture Wind Power Hydropower Biomass Fired Power generation Fuel Switching Energy Efficiency Waste to Energy Technology Upgrading in Cement Industry HFC Control NEW BASELINE METHODOLOGIES

6. Landfill Gas Capture - Vale do Rosario Bagasse Cogeneration(VRBC) Project, Brazil - Salvador Da Bahia Landfill Gas Project, Brazil - Nova Gerar landfill gas to energy project, Brazil - CERUPT Methodology for Landfill Gas RecoveryBrazil - Durban landfill-gas-to-electricity project, South Africa Biomass Power - Grid-connected Biomass Power Generation, Thailand Hydropower - Mexico- El Gallo hydro power project, Mexico HFC Control HFC incineration in HCFC production Facilities, Republic of Korea Fuel Switching Granerosplant coal to gas fuel switching project, Chile APPROVED BASELINE METHODOLOGIES

7. CDMProject developers have the following two options: Select a baseline methodology from the list of existing baseline methodologies maintained by the UNFCCC Secretariat Propose a new baseline methodology BASELINE METHODOLOGY OPTIONS

8. Justification of the choice of the methodology Description of how the methodology is applied in the context of the project activity Demonstration of emission reductions below that would occur in the absence of the CDM project Defining system boundary Assessment of the additionality STEPS TO ADOPT EXISTING BASELINE METHODOLOGY

9. - Title of the proposed methodology - Description of the methodology and its applicability - Key parameters/assumptions and data sources - Definition of the system boundary - Assessment of uncertainties - Calculation of baseline emissions and the determination of project additionality - Address any potential leakage of the project activity - Transparency and conservatism - Assessment of strengths and weaknesses of the baseline methodology - National and Sectoral Policies STEPS TO DEVELOP NEW BASELINE METHODOLOGY

10. This methodology is based on the A.T. Biopower Rice Husk Power Project in Pichit, Thailand whose Baseline study, Monitoring and Verification Plan and Project Design Document were prepared by Mitsubishi Securities. It follows Approach “B” stated in Paragraph 48 of the CDM M&P--emissions from a technology that represents an economically attractive course of action, taking into account barriers to investment--. EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand

11. This methodology is applicable to biomass-fired power generation project displacing grid electricity in the following conditions: Use of biomass that would otherwise be dumped or burned in an uncontrolled manner Have an access to an abundant supply of biomass that is unutilized and is too dispersed to be used for grid electricity generation under business as usual (BAU) Have a negligible impact on plans for construction of new power plants Not be connected to a grid with suppressed demand Have a negligible impact on the average grid emissions factor Where the grid average carbon emission factor (CEF) is lower (and therefore more conservative) than the CEF of the most likely operating margin candidate EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

12. Emissions Accounted for: Direct on site emissions: Emissions within the physical boundary of the project in the baseline that would be affected by the CDM project activities Emissions within the physical boundary of the actual CDM project activities Direct off site emissions: Emissions outside the physical boundary of the CDM project but within its system boundary in the baseline that would be affected by the CDM project activities Emissions beyond the physical boundary of the actual CDM project but within its system boundary Leakage: Increase in emissions outside the system boundary due to the CDM project activities EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

13. EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

14. Determination of Baseline The baseline assumes continued open air burning of the biomass used by the project activity and generation of electricity supplied by the project activity by other facilities. Since open air burning results in lower GHG emissions than decay of biomass, it is assumed for the baseline confirming that the baseline is conservative one. The baseline emissions (BLGHGy ) are then calculated as: BLGHGy = BBCH4y + EGCO2y BBCH4y = CH4 emissions during the year due to open air burning of the biomass used for electricity generation EGCO2y = CO2 emissions during the year due to generation of the electricity by other sources. EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

15. Determination of Baseline (Continue) BBCH4y = BFy * BCF * CH4F * CH4C * GWPCH4 BFy = biomass used as fuel during the year (metric tonnes) BCF = carbon fraction of the biomass fuel (tonnes of carbon/tonne of biomass) CH4F = fraction of the carbon released as CH4 in open air burning CH4C = mass conversion factor of CH4 (16/12) EGCO2y = EGy * CEFy EGy = electricity supplied to the grid by the project during the year (MWh) CEFy = CO2 emission factor for the electricity grid during the year (tCO2e/MWh) EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

16. Determination of Baseline (Continue) The CEFy is the lower of the grid average CO2 emission factor or the operating margin CO2 emission factor calculated ex post for the year If the project is located in a country/region with suppressed demand, the project participants may use a CO2 emission factor based on the “build margin” For simplification and favoring conservative baselines, N2O emissions from open air burning of surplus biomass is excluded. EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

17. Estimation of Emission Reductions The project reduces CH4 emissions due to the decay or burning of the biomass as well as CO2 emissions due to generation of the electricity by other sources. The project activity generates CH4 emissions due to combustion of the biomass as well as CO2, CH4 and N2O emissions due to transportation of the biomass to the generation facility and on-site. The emission reduction by the project (ERy) during a given year is:   ERy = BLGHGy - BBEGCH4y - BTGHGy - OTGHGy - FFGHGy BLGHGy = Baseline GHG emissions during the year BBEGCH4y = CH4 emissions from biomass combustion for electricity generation BTGHGy = CO2, CH4 and N2O emissions from biomass transport to project site OTGHGy = CO2, CH4 and N2O emissions from on-site biomass transportation FFGHGy = CO2, CH4 and N2O emissions from auxiliary fuel consumption EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

18. Estimation of Emission Reductions (Continue) CH4 emissions from biomass combustion for electricity generation (BBEGCH4y) BBEGCH4y= BFy * BFHV * EFCH4 * GWPCH4 BFy = biomass used as fuel (metric tonnes) BFHV = heat value of the biomass fuel used (TJ/tonne) EFCH4 = CH4 emission factor for the biomass fuel (tonnes CH4/ TJ) GWPCH4 = Approved Global Warming Potential value for CH4 (21) EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

19. Estimation of Emission Reductions (Continue) CO2, CH4 and N2O emissions from biomass transport to project site (BTGHGy) BTGHGy = BFy/TC * AVDy * [VEFCO2 + VEFCH4 * GWPCH4 + VEFN2O * GWPN2O] BFy = biomass used as fuel (metric tonnes) TC = truck capacity (tonnes of biomass) AVDy = average return trip distance between the biomass fuel supply sites and the electricity generating plant site (km) VEFCO2 = CO2 emission factor for the trucks (tCO2/km) VEFCH4 = CH4 emission factor for the trucks (tCH4/km) VEFN2O = N2O emission factor for the trucks (tN2O/km) GWPN2O = approved Global Warming Potential value for N2O (310) EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

20. Estimation of Emission Reductions (Continue) CO2, CH4 and N2O emissions from on-site biomass transportation (OTGHGy) OTGHGy = OFy * [VEFCO2 + VEFCH4 * GWPCH4 + VEFN2O * GWPN2O] OFy = transportation fuel used on-site (kg) VEFCO2 = CO2 emission factor for the transportation fuel (gCO2/kg) VEFCH4 = CH4 emission factor for the transportation fuel (gCH4/kg) VEFN2O = N2O emission factor for the transportation fuel (gN2O/kg)   FF_GHGy = FFy * [GEF_CO2 + GEF_CH4 * GWP_CH4 + GEF_N2O * GWP_N2O] EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

21. Estimation of Emission Reductions (Continue) CO2, CH4 and N2O emissions from auxiliary fuel consumption (FFGHGy)   FFGHGy = FFy * [GEFCO2 + GEFCH4 * GWPCH4 + GEFN2O * GWPN2O] FFy = fossil fuel used by the electricity generating unit as start-up and auxiliary fuel (TJ) GEFCO2 = CO2 emission factor for the generating unit (tCO2/TJ) GEFCH4 = CH4 emission factor for the generating unit (tCH4/TJ) GEFN2O = N2O emission factor for the generating unit (tN2O/TJ) N2O emission from grid electricity generation is excluded for simplification and to favor the conservative baseline EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

22. Additionality Testing Barrier Analysis: The project could not be materialized in the absence of CDM due to the presence of following barriers: Investment barriers Technological barriers Barriers due to prevailing practice Other barriers EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

23. Additionality Testing (Continue) Investment barriers Return on equity is too low as compared to conventional projects Real and/or perceived risk associated with the unfamiliar technology or process is too high to attract investment Funding is not available for innovative projects Technological barriers The project represents one of the first applications of the technology in the country, leading to technological concerns even when the technology is proven in other countries Skilled and/or properly trained labor to operate and maintain the technology is not available EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

24. Additionality Testing (Continue) Barriers due to prevailing practice There is a lack of will to change the current biomass disposal practice with or without regulations Developers lack familiarity with state-of-the-art technologies and are reluctant to use them Other barriers Management lacks experience using state-of-the-art technologies, so such projects require too much management time and receive low priority by management The local community may fail to see the environmental benefits of biomass power generation and so may oppose the project EXAMPLES OF BASELINE METHODOLOGYAM0004: Grid-connected Biomass Power Generation that avoids Uncontrolled Burning of Biomass, Thailand (Cont…)

25. A large number of commercially available energy models (e.g., MARKAL, ENPEP LEAP) are now adopted to estimate GHG emissions resulted from energy supply and demand activities. These models could be applicable in estimating baseline emissions in various types of CDM projects (e.g., . ENPEP for power sector projects; LEAP for demand side or energy efficiency improvements projects; MARKAL for supply side projects) These models are, however, more appropriate in setting baselines at the sectoral and national levels; their use for estimating baselines for a particular CDM project activity (or setting project specific baseline) depends on size of the project. (GHG emissions from a CDM project activity could be negligible compared to sectoral or national level emissions) MODELS FOR BASELINE EMISSION ESTIMATIONS

26. MARKAL (acronym for MARKet ALlocation) is a bottom-up type model developed by the Energy Technology Systems Analysis Program (ETSAP) of the International Energy Agency (IEA) It is a linear programming type optimization model and based on Reference Energy System (RES) energy system from primary energy resources through conversion processes, to transport, distribution and end - use devices. Demand and supply are balanced through optimization Detailed modeling of energy supply side Detailed representation of resources is possible Electricity sector is modeled (generation and transmission system expansion)     MODELS FOR BASELINE EMISSION ESTIMATIONS (MARKAL)

27. Source: Tseng, p. (2002), An Overview of US MARKAL-MACRO Model, US Department Of Energy, Washington MODELS FOR BASELINE EMISSION ESTIMATIONS (MARKAL Cont…)

28. ENPEP MODEL ENPEP (Energy and Power Evaluation Program) is a set of 10 integrated energy, environmental, and economic analysis tools (developed for IAEA). MACRO-E Economic impacts MAED Energy demandforecasting LOAD Hourly load profiles and load duration curves PC-VALORAGUA Optimal generating strategy for hydro-thermal systems WASP-IV Least-cost generating system expansion path GTMAX Generation and transmission maximization module ICARUS Costs and reliability in utility systems module IMPACTS Physical and economic damages from air pollution BALANCE Demand respond to price changes DAM Decision analysis for technical, economic, and environmental tradeoffs MODELS FOR BASELINE EMISSION ESTIMATIONS (ENPEP)

29. Detailed evaluation of the sectoral energy demands by sector, sub-sector, fuels and useful energy Representation of resource availability and costs Detailed evaluation of the power system configurations both current and future Equilibrium solution for total energy system, energy policy constraints can be imposed Environmental impacts under baseline and environmental scenarios    MODELS FOR BASELINE EMISSION ESTIMATIONS (ENPEP Cont…)

30. MODELS FOR BASELINE EMISSION ESTIMATIONS (ENPEP Cont…) Emission Estimation Using ENPEP

31. LEAP (Long Range Energy Alternatives Planning System) is developed by Stockholm Environmental Institute - Boston, USA. In contrast to MARKAL and ENPEP, LEAP is not an optimization model, rather it is a scenario-based energy accounting model. Detailed evaluation of the sectoral energy demands by sectors, sub-sectors end-uses and equipment. Simulation of any energy conversion sector (e.g., electric generation, oil refining, charcoal making) Detailed evaluation of supply configurations both current and future periods Iterative calculation of demand/supply balance It accommodates a Technology and Environmental Database MODELS FOR BASELINE EMISSION ESTIMATIONS (LEAP)

32. MODELS FOR BASELINE EMISSION ESTIMATIONS (LEAP Cont..)

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